Trends In Minimum Temperatures Research Articles

Future climate change projections in the agroecological, bioclimatic, biogeographical and altitudinal vegetation zones of Morocco

AbstractMorocco is located in a region vulnerable to the impacts of climate change, which can have profound effects on its social, economic and environmental systems. This makes studies aimed at forecasting these impacts in future using climate models particularly important. However, the generally coarse spatial resolution of models, combined with a large number of models, imposes a limitation on the models, allowing the selection of the most appropriate ones for climate change impact assessments in a specific region. In this study, 38 GCMs and GCM‐RCMs from CMIP5 ensemble and CORDEX project were downscaled and bias‐corrected for use in projecting climate change over Morocco under the RCP4.5 and RCP8.5 scenarios. A three‐step sequential process was adopted, involving in that order the selection of models based on: (i) projection of climate means; (ii) projection of climate extremes; and (iii) ability of the models to simulate the baseline climate. Climate projections show precipitation decreases of up to 10% by the beginning of the century, with decreases of more than 20% under RCP8.5 projected by 2100, with the central and northern mountainous regions of the country being the most affected. Seasonal projections showed autumn months likely to experience the greatest decline in precipitation, up to 36.56% by the end of the century. Temperature projections revealed an upward trend in mean, maximum and minimum temperatures, with increases of up to 3°C predicted by mid‐century over most of the country, particularly in the winter months. Our results point to a concerning future, with impacts related to decreased precipitation and increased temperatures expected to be many and varied across the country. Nevertheless, they can help provide a knowledge base for efforts to mitigate and adapt to expected changes.

Trends in minimum winter temperatures and date of the last spring frost in the main fruit-growing areas of Spain

Trends in minimum winter temperatures and date of the last spring frost in the main fruit-growing areas of Spain

Protected Areas Conserved Forests from Fire and Deforestation in Vietnam’s Central Highlands from 2001 to 2020

As a tropical nation with ~40% forested land area and 290 protected areas in the Indo-Burma Biodiversity Hotspot, Vietnam holds an important part of global forests. Despite a complex history of multiple colonial rules, war, rapid economic development and societal growth, Vietnam was one of a few Southeast Asian countries to reverse deforestation trends and sustain net forest cover gain since the 1990s. However, a considerable amount of Vietnam’s forest gain has been from plantation forestry, as Vietnam’s policies have promoted economic development. In the Central Highlands region of Vietnam, widespread forest degradation and deforestation has occurred recently in some areas due to plantation forestry and other factors, including fire-linked deforestation, but protected areas here have been largely effective in their conservation goals. We studied deforestation, wildfires, and the contribution of fire-linked deforestation from 2001 to 2020 in an area near the Da Lat Plateau of the Central Highlands of Vietnam. We stratified our study area to distinguish legally protected areas and those in the surrounding landscape matrix without formal protection. Using satellite-derived data, we investigated four questions: (1) Have regional deforestation trends continued in parts of the Central Highlands from 2001 to 2020? (2) Based on remotely sensed fire detections, how has fire affected the Central Highlands and what proportion of deforestation is spatiotemporally linked to fire? (3) Were annual deforestation and burned area lower in protected areas relative to the surrounding land matrix? (4) Was the proportion of fire-linked deforestation lower in protected areas than in the matrix? To answer these questions, we integrated the Global Forest Change and FIRED VIETNAM datasets. We found that 3794 fires burned 8.7% of the total study area and 13.6% of the area became deforested between 2001 and 2020. While nearly half of fires were linked to deforestation, fire-linked deforestation accounted for only a small part of forest loss. Across the entire study area, 54% of fire-linked deforestation occurred in natural forests and 46% was in plantation forests. Fire ignitions in the study area were strongly linked to the regional dry season, November to March, and instrumental climate data from 1971 to 2020 showed statistically significant increasing trends in minimum, mean, and maximum temperatures. However, the total area burned did not have a significant increasing trend. Regional trends in deforestation continued in Vietnam’s Central Highlands from 2001 to 2020, and nearly half of all detected fires can be spatially and temporally linked to forest loss. However, protected areas in the region effectively conserved forests relative to the surrounding landscape.

Future transition in climate extremes over Western Ghats of India based on CMIP6 models.

The effect of climate change on the tropical river catchments in the Western Ghats of India is studied using the Coupled Model Intercomparison Project-6 data (CMIP-6). Multi-model ensembles of rainfall and temperature are constructed using the Random Forest ensemble technique for bias-corrected GCMs in the near future (2014-2050) and far future (2051-2100) horizons. For the two catchments each in the southern, central, and northern Ghats, the trend in minimum and maximum temperatures, precipitation, and other indices are calculated. By 2100, dry sub-humid and humid catchments will see a higher increase in mean annual temperature than per-humid central catchments. In future decades, the warm days and nights increase by 45-50% and 40-70%, respectively, with twofold warming in the winter season. Under a climate change scenario, annual rainfall increases in Vamanapuram, Ulhas, and Purna, while Chaliyar, Netravati, and Aghanashini catchments experience a decrease in rainfall in the far future with an increase in pre-monsoon rainfall. The southern catchments are anticipated to have contrasting variations in the rainfall extremes; northern catchments face a substantial increase in very wet to extremely wet days and medium to heavy rainfall. In all catchments (excluding Vamanapuram), cumulative wet days increase with a decrease in cumulative dry days. After the mid-twenty-first century, humid to per-humid catchments encompass an increase in cool nights, whereas it disappears in dry sub-humid catchments of the Ghat. Interestingly, warming tendencies begin to slow down after 2050. This investigation can assist in comprehending the regional climate extremes in the Western Ghats to formulate better climate risk planning and adaptation strategies.

Case study of rainfall and temperature assessment through trend and homogeneity analyses in Vadodara and Chhotaudepur district of Gujarat State, India

This study aims to assess the climate change impact on the rainfall and temperature data of the Vadodara-Chhotaudepur district of India and to focus on the environmental challenges related to the rainfall and temperature in the present state of development, land use, industrialization, and urbanization. The study utilized nine trend analysis methods, namely linear regression (LR), Sen's robust slope estimator (SS), Mann-Kendall test (MK), Spearman's rank correlation (SRC), the trend-free pre-whitening (TFPW), variance correction approach by Hamed and Rao (1998) with MK test (MK-CF1), variance correction approach by Yue and Wang (2004) with MK test (MK-CF2), block bootstrap with MK test (BBS-MK), and graphical method as innovative trend analysis (ITA), applied on monthly, annual, and seasonal scales. Additionally, the study also employed four homogeneity analysis methods, including Pettitt's test, standard normal homogeneity test (SNHT), Buishand's test, and Von Neumann Ratio test (VNRTs). The IMD (Indian meteorological department) gridded long-term rainfall data from 1901 to 2019 and temperature data from 1951 to 2019 are used in the present study to assess the homogeneity and trends of the data series. Results showed a warming trend of maximum temperature (MaxT) and minimum temperature (MinT) at the monthly, annual, and seasonal time scale and significant (at 5%) warming trend in annual MinT in the entire study area. Annual rainfall showed negative trend in the study area with significant (at 5%) negative trend in eastern deforested area western industrial and area adjacent to thermal power station. The change point is detected in annual rainfall time series in eastern forest area in 1959 and western area in 1983, i.e., after development of the industries and commissioning of thermal power station in the western study area. The trend rate of MaxT and MinT has been recognized as 0.004°C/year and 0.019°C/year, respectively, for the data period of 1951 to 2019. The annual rainfall trend rate has been observed as -0.743mm/year for the data range 1901 to 2019. All trend analysis methods revealed consistent results except MK-CF2 method, which portraits greater number of significant trends in trend analysis methods.

Temporal Changes in Minimum and Maximum Temperatures at Selected Locations of Southern Africa

Agriculture is threatened by ever increasing temperatures and this trend is predicted to continue for the near and distant future. The negative impact of rising temperatures on agri-food systems is also compounded by the erratic and highly variable rainfall in most parts of southern Africa. Minimum and maximum temperatures’ variability and trend analysis were undertaken using daily time series data derived from 23 meteorological stations spread across Malawi, Mozambique, South Africa and Zimbabwe. The modified Mann–Kendall and Theil–Sen slope models were used to assess temperature trends and their magnitudes. Temperature varied with location and minimum temperature was more variable than maximum temperature. Semi-arid regions had higher variation in minimum temperature compared to humid and coastal environments. The results showed an upward trend in minimum (0.01–0.83 °C over a 33–38 year period) and maximum (0.01–0.09 °C over a 38–57 year period) temperatures at 9 and15 locations, respectively. A downward trend in minimum temperature (0.03–0.20 °C over 38–41 years) occurred in South Africa at two locations and Dedza (Malawi), while a non-significant decline in maximum temperature (0.01 °C over 54 years) occurred at one location in coastal dry sub-humid Mozambique. The results confirm the increase in temperature over 33–79 years, and highlight the importance of including temperature when designing climate change adaption and mitigation strategies in southern Africa and similar environments.

Changing Trends in Temperatures and Rainfalls in the Western Pacific: Guam

Pacific islands have always been at the front of the great challenge of climate change. In this study, Mann–Kendall’s tau-based slope estimator was implemented to detect statistical trends in daily maximum and minimum temperatures of 2 stations and daily rainfalls at 14 stations over Guam for the period of 1953–2021, respectively, with 17 climate change detection indices. Mann–Kendall tests were implemented to the detection indices with respect to different time frames (i.e., annual, two-seasonal, and four-seasonal). The p-values from Mann–Kendall tests were used to determine the strength of trends, and Sen’s slopes were applied for the magnitudes of trends. The temperature trend analysis results indicate that Guam’s climate is getting warmer year by year. The increasing magnitudes of a seasonal maximum of daily maximum temperatures during the dry season are 0.036 °C/year for the dry season and 0.025 °C/year for the wet season at Anderson Airforce Base, while 0.031 °C/year and 0.023 °C/year for the dry and wet seasons at Guam International Airport. Trend analyses for temperatures have indicated that temperature during April through June has been increasing rapidly compared to other seasons. Strong trends in seasonal total rainfall amounts and the number of wet days were observed from July through December. The increasing trends in extreme rainfall indices during January–March and July–September periods would aggravate water quality due to the more sediments since important ecological reserve areas and coral reef areas are linked to watersheds in southern Guam.

Spatial and Temporal Trend Analysis for Maximum and Minimum Temperature Using Non-Parametric Techniques

A study on annual and seasonal (winter, spring, summer, and autumn) trend analysis of maximum and minimum temperature at the spatial and temporal scales had been carried out during January, 1981 to December, 2020 for agro-climatic zone-III of Bihar, India. Non-parametric statistical techniques viz. Mann-Kendall (MK) test with Sen’s slope estimator, and Pettitt Mann–Whitney (PMW) test had been carried out to examine the annual and seasonal trends at 5% level of significance. The monthly air temperature (°C) from the period January, 1981 to December, 2020 had been recorded for the spatial and temporal trend analysis. The results of the nonparametric tests showed statistically significant increasing trends in summer, autumn, and spring seasons for minimum temperature at most the spatial horizons while the trends for maximum temperature showed statistically non-significant decreasing trends at all the spatial horizons. The rate of change of the minimum temperature obtained from Sen’s slope estimator was found to be higher in summer (0.021°C year-1), autumn (0.054°C year-1), and spring (0.041°C year-1) seasons at Bhojpur district. In case of the maximum temperature, the rate of change of temperature was observed to be higher in annual (-0.020°C year-1), winter (-0.012°C year-1), summer (-0.019°C year-1), and autumn (-0.013°C year-1) seasons. The most probable year of changes in the observed temperature were occurred in between 1992–2010. In conclusion, it was clear that the magnitudes of the minimum temperature trends and variability is greater than the maximum temperature for all 6 spatial horizons.

Malaria hotspots and climate change trends in the hyper-endemic malaria settings of Mizoram along the India–Bangladesh borders

India has made tremendous progress in reducing malaria mortality and morbidity in the last decade. Mizoram State in North-East India is one of the few malaria-endemic regions where malaria transmission has continued to remain high. As Mizoram shares international borders with Bangladesh and Myanmar, malaria control in this region is critical for malaria elimination efforts in all the three countries. For identifying hotspots for targeted intervention, malaria data from 385 public health sub-centers across Mizoram were analyzed in the Geographic Information System. Almost all the sub-centers reporting high Annual Parasite Index (> 10) are located in Mizoram’s districts that border Bangladesh. Getis-Ord Gi* statistic shows most of the sub-centers located along the Bangladesh border in the Lawngtlai and Lunglei districts to be the malaria hotspots. The hotspots also extended into the Mamit and Siaha districts, especially along the borders of Lawngtlai and Lunglei. Analysis of terrain, climatic, and land use/land cover datasets obtained from the Global Modelling and Assimilation Office and satellite images show Mizoram’s western part (Lawngtlai, Lunglei, and Mamit districts) to experience similar topographic and climatic conditions as the bordering Rangamati district in the Chittagong division of Bangladesh. Climatic trends in this region from 1981 to 2021, estimated by the Mann–Kendall test and Sen's slope estimates, show an increasing trend in minimum temperature, relative humidity, rainfall, and the associated shift of climatic pattern (temperate to tropical monsoon) could facilitate malaria transmission. The quasi-Poisson regression model estimates a strong association (p < 0.001) between total malaria cases, temperature range, and elevation. The Kruskal–Wallis H test shows a statistically significant association between malaria cases and forest classes (p < 0.001). A regional coordination and strategic plan are required to eliminate malaria from this hyper-endemic malaria region of North-East India.

Spatio-temporal Fluctuation of Temperature Using Specific Climate Indices in South Xinjiang, China

Temperature and precipitation are significant variables that can be used to determine the climatic variability in a region. This research study has focused on temperature, which is significant for the study of climatic variability over a long period in an area. The temperature has been assessed spatially and temporally in South Xinjiang, China using various climate indices. The temporal data about the temperature of seventeen meteorological stations were acquired from the Chinese Meteorology Administration (CMA) from 1980 to 2018. The Mann-Kendall (MK) trend test and Sen’s Slope (SS) statistical models were used to quantify the magnitude and temporal trend. The monthly and seasonal analysis of temperature reveals a significant increasing trend in mean maximum, mean minimum and average temperatures in the study area. The Sen’s Slope test results indicate an increasing monthly and seasonal temperature trend in almost all meteorological stations. The increasing trend in temperature is mainly due to the desert type of climate of the region that is gradually further aggravating with every passing year. This increasing temperature trend will smoothen the way for perpetual drought in the region in the future. Therefore, this research would be beneficial for future planning and management of water resources in the region and for making preventive measures to mitigate the impacts of climate change in the study area.

Understanding Changes in the Hydrometeorological Conditions towards Climate-Resilient Agricultural Interventions in Ethiopia

Climate resilient agriculture (CRA) is very important to achieve long-term improvement in productivity and farm incomes under climate uncertainty. The present study focuses on investigating the plausible changes in the hydrometeorological conditions using big-data analysis techniques in the study of Ethiopia. The original contribution of this work envisages the importance of the CRA system in water-scarce areas for sustainable agriculture planning and management under changing climatic conditions. In the present research, a TerraClimate model was the basis for weather (precipitation and temperature) and hydrological data (runoff, actual evapotranspiration, potential evapotranspiration, vapor pressure deficit and climate water deficit); these data were used to determine the spatial distribution of the standardized anomaly index (SAI) and the slope of the linear regression for long-term (1958–2020) trend analysis. Future climate trend analysis (2021–2100) has been performed through the CMIP6 (EC-Earth3) shared socio-economic pathway (SSP 2) 4.5 dataset. Gravity Recovery and Climate Experiment (GRACE) with CSR and JPL data were utilized for the generation of water storage heat maps from 2002 to 2021. The results show that the average annual rainfall data for over 62 years was found to be 778.42 mm and the standard deviation is 81.53 mm. The results also show that the western part of the study area has the highest temperature trend, which diminishes as one moves eastward; the minimum temperature trend has been found in the western part of the study area. It was found that the equivalent water thickness (EWT) range of both CSR and JPL products was −15 to 40 cm. These results can help local climate-resilient development planning and enhance coordination with other institutions to access and manage climate finance.

Increasing Risk of Spring Frost Occurrence during the Cherry Tree Flowering in Times of Climate Change

Climate change affects the agroecological conditions and persistence of cherry tree flowering. Detailed evaluation of minimum air temperature and occurrence of synoptic events occurrence during spring frosts within the cherry tree flowering in the Czech Republic (Central Europe) is missing. The main objective of this study was to evaluate the above-mentioned variables during the cherry tree flowering in different parts of the country from 1924 to 2012. Our question was how the frequency of frost days occurrence changed during the cherry tree flowering. A trend analysis was conducted with the Mann-Kendall test. The onset of the beginning of flowering and end of flowering shifted to an earlier date per the whole examined period (up to −13.9 and −8.1 days) and the period of flowering extended (up to 4.1 days). The shifts were more pronounced at higher elevations. During the period of the cherry tree flowering, the trend in change of the number of frost days was negative at the lowland station (−0.3 day) and positive at the highland station (+1.2 day). At all stations, “Ap3” synoptic event (anticyclone) occurrence during cherry tree flowering on days with the highest spring frost risk (Tmin at 2 m &lt; −1.1 °C) prevailed. The positive trend of frost-day occurrence and the negative trend of minimum air temperature in cherry tree flowering indicate that blossoms are more endangered at higher elevations.

Recent Trends of Mean Maximum and Minimum Air Temperatures in Bangladesh

The annual, seasonal, and monthly maximum and minimum air temperature time series for 34 stations in Bangladesh have been examined during the period 1981– 2020 in this study. Three statistical tests were used in the analysis namely Mann–Kendall, Sen’s slope estimator, and linear regression, respectively. 47% of stations experienced significantly rising maximum air temperature trends during the pre-monsoon, 100% during the monsoon, 74% during the post-monsoon, and 24% during the winter season, respectively. Similar findings have been made about minimum air temperatures during the pre-monsoon, monsoon, post-monsoon, and winter seasons in 41, 91, 41, and 35% of stations over Bangladesh. According to the linear regression technique, the significant increasing trends of the maximum air temperatures at Patuakhali and Mongla stations are 0.83°C/decade and 0.82°C/decade in February and October, respectively. Furthermore, at Sandwip and M. Court, the significant increasing minimum air temperature trends in July and March are 0.26°C/decade and 0.66°C/decade, respectively. The highest monthly maximum and minimum air temperature time series value falls (decreases) were seen in January over the stations at Mongla (-0.58°C/decade) and Sandwip (-0.63°C/decade), respectively. This information will be useful in developing adaptation plans to mitigate the harmful effects of climate change. Vulnerability assessments, disaster management, enhanced structure design, institutional reform, and antiextreme climate engineering are some of the viable climate change adaptation approaches in Bangladesh due to rising temperatures.

Analysis of meteorological parameter changes using Mann-Kendall statistical tests in Indian Punjab

Groundwater in Central Punjab is declining at an alarming rate of one meter annually in last two decades and likely to be exhausted up to 300 meter depth in next 2-3 decades as per recent report published in 2018 based upon exhaustive analysis done till 2017 by the relevant agencies (Anonymous, 2018). All the blocks in this zone are over exploited. Rainfall and temperature are predominant meteorological parameters which influence irrigation demand which in turn influences ground water withdrawal; which ultimately influence groundwater depth in the region. Area under rice is increasing due to high returns. So, the trend analysis of these parameters is of paramount importance for sustainability of agriculture in this region. The aim of the present investigation was to study annual trend of precipitation, maximum and minimum temperature and rainfall for 10 locations in Central Punjab during 1998–2019. The effect of rainfall and rice area on groundwater depth has been also studied. To achieve this non-parametric Mann-Kendall and Sen's applied to the data series of annual rainfalls, annual maximum and minimum temperature of the ten selected stations. The nonparametric statistical tests applied to series of annual Tmax revealed an increasing trend in all of the locations of the study area. According to results by Sen’s slope estimator, the increasing trend in annual precipitation series was detected at the Tarantaran, Kapurthala,Ludhiana, Moga, Barnala and Jalandhar, while other stations had negative or no trends.

Spatiotemporal analysis of temperature and precipitation extremes over Bangladesh using a novel gridded observational dataset

This study explores spatial changes in trends of 29 climate extremes indices between 1981 and 2020 in Bangladesh, a country that frequently experiences the impacts of extreme events. This is the first study to examine trends in extreme climate over Bangladesh using a high resolution (0.05° × 0.05°) gridded daily temperature and precipitation data rather than individual stations. Trends in mean daily maximum and minimum temperatures were +0.38 °C and +0.25 °C per decade, respectively, for the last 40 years. The maximum increases in both warm days and nights were 12.75 days per decade with the fastest rate of warming in the eastern part of the country, whereas the maximum decreases in both cold days and nights were 7 days per decade with the western part experiencing the greatest increase in extreme cold. Significant reductions in total precipitation (225 mm per decade) were observed in the major parts of the country. However, the number of very heavy precipitation days (R20mm) showed a statistically significant increase (2.25 days per decade) in the southern coastal areas, with the tendency of more extreme wet days (R30 mm). The maximum decrease in annual total precipitation was 225 mm per decade while the consecutive dry days increased by 12.5 days per decade. While previous studies reported a faster rise in minimum temperature than maximum temperature, this study shows a faster increase in maximum temperature instead of minimum temperature in the study area. Extreme temperature changes were statistically more significant than changes in extreme precipitation. This study also shows statistically significant and consistent spatial trends of extreme temperature and precipitation when using high-resolution gridded observational datasets instead of station data.

Reconstruction of post-little ice age glacier recession in the Lahaul Himalaya, north-west India

ABSTRACT Understanding past glaciation and deglaciation is vital for assessing present-day glacier dynamics and response to climate change. We focus on reconstructing past glacier fluctuations in Lahaul, north-west India, a region located between arid Ladakh and the humid the Pir-Panjal range. We focus specifically on six glaciers in the Miyar and Thirot catchments of varying size, aspect and debris cover. To reconstruct past terminus fluctuations of these glaciers, we used repeat terrestrial photography and historical archives as data sets and mapped the terminus positions and latero-terminal moraines in the field along with glacier terminus mapping from high to medium resolution satellite images (e.g. Corona, Hexagon, Landsat and LISS IV). Results show that since the little ice age, all the studied glaciers have experienced terminus retreat and area loss, with average values of 1.46 and 0.9 km2, respectively. Precipitation data show a statistically significant decreasing trend during the last century with an increasing trend in annual average maximum (T max) and minimum (T min) temperature. This warming trend is more statistically significant for T min. Although total ice loss at the six studied glaciers is considerable (5.48 km2), this varies both spatially (i.e. from glacier to glacier) and temporally. We attribute this variability to topographic controls such as glacier hypsometry and another non-climatic factor, i.e. varying degree of debris cover.

Weekly Trend Detection in Meteorological Data for Crop Response

Climate is perceived to be changing worldwide and there has been growing concern towards the direction and magnitude of these changes. Greenhouse gases are responsible for maintaining earth's surface temperature suitable for sustaining life, but excess emission of GHGs increase the earth’s surface temperature and causing global warming. Globally, over the past several decades, about 80% of human-induced carbon dioxide emissions came from the burning of fossil fuels, while about 20% from deforestation and associated agricultural practices. The objective of the study are to document the ability of the turning test, MK test, Sen’s Slope and Spearman rank correlation to detect the weekly trend, and to discuss the different between statically significance and practical significance. Conclusions are parted in different season like Kharif, Rabi and Summer season. In which, overall found that the minimum temperature trend is increases during kharif season. In Rabi season the both temperature are increase so at that time the CWR requirements are more. If the minimum temperature is increase its effect on crops (Wheat and cumin) growth and yield is decrease in summer season. The high temperature from flowering and from podding increase flower numbers, but reduced fruit set, resulting in reduction in reproductive number, pod number and pos yield. High temp also reduced the total dry matter when imposed at flowering, but not at podding. However, pod weights were reduced by high air temperature during the flowering and podding.

Rainfall and Temperature Trends and Variability in Arid and Semi-arid Lands of Kitui County, Kenya

A study was carried out to analyse rainfall and temperature trends and variability in selected agro-ecological zones in Kitui County. Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) rainfall dataset was used while temperature data was obtained from the Climatic Research Unit gridded Time Series (CRU TS) dataset. The results indicated that there was a non-significant decreasing trend (p&lt;0.05) in average annual rainfall in all the four agro-ecological zones (p&lt;0.05) for a 30-years period (1988-2018) in the study area. A decreasing trend in March-April-May (MAM) seasonal rainfall trend was reported in the arid and semi-arid agro-ecological zones while an increasing trend was recorded in the transitional and semi-humid zones. For the October-November-December (OND) seasonal rainfall, a non-significant decreasing trend was reported in all the four agro-ecological zones. Additionally, a higher annual rainfall variability was recorded in the drier (arid) and wetter (semi-humid) zones compared to that in semi-arid and transitional zones. Moreover, the study established that there was a spatial variation in both MAM and OND seasonal rainfall variability and that rainfall variability was higher in the OND seasonal rainfall than that of the MAM seasonal rainfall in all the agro-ecological zones. With reference to temperature trends, a statistically significant increasing trend in annual and OND seasonal average maximum and minimum temperatures was reported in all the four agro-ecological zones. Further, the study noted a non-significant increasing trend in maximum and minimum temperatures for the MAM season in all the agro-ecological zones. In regard to temperature variability, the study deduced that there was low temperature variability compared to rainfall variability in all the four agro-ecological zones. The study recommends that location-specific rainfall and temperature analysis should guide planning and implementation of adaptation strategies for effective response to climate variability. Keywords: Agro-ecological Zones, Mann-Kendall Test, Coefficient of Variation, CHIRPS, CRU TS DOI: 10.7176/JEES/12-12-05 Publication date: December 31 st 2022

Temperature characteristics and heat load in the City of Dubrovnik

In this study, temperature characteristics and heat load in the city of Dubrovnik are investigated by using temperature data observed at the local meteorological station in Dubrovnik for the period 1961-2019, satellite data collected by LANDSAT5 satellite for the period 2001-2010, and climate indices data obtained from simulations of an urban climate model (MUKLIMO_3) for the period 2001-2010. Trends in daily mean, maximum, minimum, and seasonal temperatures were analysed by using Sen's slope and the Mann-Kendall test. Results reveal rising trends for all of the studied temperature-related elements. However, it is demonstrated that temperature increase is greatest for the summer season with the highest rise for daily maximum temperatures. The same approach was applied to examine trends of climate indices (summer days and tropical nights), which indicates an increase in the number of both summer days and tropical nights. Results of satellite data of average summer land surface temperatures for the period 2001-2010 indicate that urbanised surfaces and bare rock areas heat up more than natural surfaces with vegetation. Climate indices (summer and hot days, warm evenings, and tropical nights) simulated by the urban climate model MUKLIMO_3 also reveal that, on average, in the city of Dubrovnik urbanised surfaces heat up more than natural surfaces with vegetation and that nocturnal heat load is reduced in lower-density built-up areas.

Trends in Temperature-associated Mortality in São Paulo (Brazil) between 2000 and 2018: an Example of Disparities in Adaptation to Cold and Heat

Exposure to non-optimal temperatures remains the single most deathful direct climate change impact to health. The risk varies based on the adaptation capacity of the exposed population which can be driven by climatic and/or non-climatic factors subject to fluctuations over time. We investigated temporal changes in the exposure–response relationship between daily mean temperature and mortality by cause of death, sex, age, and ethnicity in the megacity of São Paulo, Brazil (2000–2018). We fitted a quasi-Poisson regression model with time-varying distributed-lag non-linear model (tv-DLNM) to obtain annual estimates. We used two indicators of adaptation: trends in the annual minimum mortality temperature (MMT), i.e., temperature at which the mortality rate is the lowest, and in the cumulative relative risk (cRR) associated with extreme cold and heat. Finally, we evaluated their association with annual mean temperature and annual extreme cold and heat, respectively to assess the role of climatic and non-climatic drivers. In total, we investigated 4,471,000 deaths from non-external causes. We found significant temporal trends for both the MMT and cRR indicators. The former was decoupled from changes in AMT, whereas the latter showed some degree of alignment with extreme heat and cold, suggesting the role of both climatic and non-climatic adaptation drivers. Finally, changes in MMT and cRR varied substantially by sex, age, and ethnicity, exposing disparities in the adaptation capacity of these population groups. Our findings support the need for group-specific interventions and regular monitoring of the health risk to non-optimal temperatures to inform urban public health policies.